基于粒子群优化算法的高阶广义屏偏移成像（英文）

High-order generalized screen propagator migration based on particle swarm optimization

频率-波数域单程波算子能高效地模拟地震波在复杂介质中的传播,但是在描述波的大角度传播和速度横向扰动变化较大介质中传播的问题时仍然存在一定误差。这类误差是由于对单平方根算子使用Taylor展开式的近似程度不足所造成。为了进一步提高泰勒展开式的精确性,本文提出一种利用粒子群智能算法优化级数展开系数的高阶广义屏算子对单平方根算子的展开级数进行优化处理。新的偏移算法能在保持单程波偏移算法高效的前提下进一步提高偏移算子在大角度的成像精度和对强横向速度变化介质的适应性。通过脉冲响应实验,验证了基于粒子群算法优化级数的高阶广义屏算子能够提高常规的高阶广义屏算子的成像精度和成像角度。根据对二维SEG/EAGE盐丘模型的成像处理,基于粒子群算法优化级数的高阶广义屏算子对盐丘下面的断层取得了更高质量的成像,说明粒子群优化级数的高阶广义屏算子比常规的高阶广义屏算子具有更好的横向速度适应性。为了检验本文所提算法对实际资料的处理能力,我们利用常规的偏移处理技术和本文所提算法对一条海上二维数据进行了偏移成像处理,对比分析成像剖面发现本文所提算法描述了更加清晰的层位信息和更高质量的偏移剖面。本文所提算法能有效提高高阶广义屏偏移在广角度成像的能力,具有一定实际应用价值。

Various migration methods have been proposed to image high-angle geological structures and media with strong lateral velocity variations; however, the problems of low precision and high computational cost remain unresolved. To describe the seismic wave propagation in media with lateral velocity variations and to image high-angle structures, we propose the generalized screen propagator based on particle swarm optimization （PSO-GSP）, for the precise fitting of the single-square-root operator. We use the 2D SEG/EAGE salt model to test the proposed PSO-GSP migration method to image the faults beneath the salt dome and compare the results to those of the conventional high-order generalized screen propagator （GSP） migration and split-step Fourier （SSF） migration. Moreover, we use 2D marine data from the South China Sea to show that the PSO-GSP migration can better image strong reflectors than conventional imaging methods.